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On Pattern-Cladistic Analyses Based on Complete Plastid Genome Sequences.

Evgeny V Mavrodiev1, Alexander Madorsky2

  • 1Florida Museum of Natural History, University of Florida, Gainesville, FL, USA. evgeny@ufl.edu.

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This study revives Hennigian principles for plant phylogenetics using complete plastid genomes (plastomes). Pattern-cladistics and a new program (Matrix to Newick) simplify analyses, offering a powerful alternative to complex methods.

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Average consensusAverage consensus analysisChloroplast genomes (plastomes)Median supertreesPattern-cladisticsRelationshipsThree-taxon statement analysisThree-taxon statements

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Area of Science:

  • Phylogenetics
  • Molecular Systematics
  • Bioinformatics

Background:

  • Modern phylogenetics often deviates from the fundamental Hennigian principle of grouping solely by synapomorphy.
  • Plastid genome (plastome)-based DNA sequence data has become increasingly popular in molecular systematics.
  • Current phylogenetic analyses of massive plastome datasets often employ complex Maximum Likelihood or Bayesian frameworks.

Purpose of the Study:

  • To reanalyze five datasets of 197 complete plastid genomes using the Hennigian principle of synapomorphy.
  • To demonstrate the effectiveness of pattern-cladistic analyses for resolving plant taxa affinities.
  • To introduce a novel program, "Matrix to Newick" (M2N), for simplifying plastome data representation and analysis.

Main Methods:

  • Reanalysis of five datasets comprising 197 complete plastid genomes.
  • Application of pattern-cladistic analyses based on Hennigian principles.
  • Development and utilization of the "Matrix to Newick" (M2N) program to convert molecular alignments to relational tree forms.
  • Employing median supertree construction (Average Consensus) and Maximum Parsimony on relational data representations.

Main Results:

  • Pattern-cladistic analyses using complete plastid genomes successfully resolved affinities between plant taxa.
  • The "Matrix to Newick" program effectively represents massive plastome data in a relational format, simplifying genomic and analytical frameworks.
  • Relational representations allow for phylogenetic analyses (e.g., Average Consensus, Maximum Parsimony) that bypass complex assumption-based methods.
  • Significant amounts of genomic information can be effectively omitted by focusing on pattern-cladistics or relational analyses.

Conclusions:

  • The proposed pattern-cladistic approach offers a powerful and straightforward heuristic alternative for modern plastome-based phylogenetics.
  • Simplifying analytical frameworks through relational data representation is feasible and effective.
  • Revisiting fundamental phylogenetic principles with new data and tools can yield significant advancements.